Network approach to patterns in stratocumulus clouds

Glassmeier, Franziska; Feingold, Graham

doi:10.1073/pnas.1706495114

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Network approach to patterns in stratocumulus clouds

2017
By Glassmeier, Franziska ; Feingold, Graham
Source: Proceedings of the National Academy of Sciences of the United States of America, 114(40), 10578-10583.

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Journal Title:

Proceedings of the National Academy of Science of the United States
Personal Author:

Glassmeier, Franziska ; Feingold, Graham

Glassmeier, Franziska ; Feingold, Graham Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; ESRL (Earth System Research Laboratory) ; CSL (Chemical Sciences Laboratory)

OAR (Oceanic and Atmospheric Research) ; ESRL (Earth System Research Laboratory) ; CSL (Chemical Sciences Laboratory) Less -
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Stratocumulus clouds (Sc) have a significant impact on the amount of sunlight reflected back to space, with important implications for Earth's climate. Representing Sc and their radiative impact is one of the largest challenges for global climate models. Sc fields self-organize into cellular patterns and thus lend themselves to analysis and quantification in terms of natural cellular networks. Based on large-eddy simulations of Sc fields, we present a first analysis of the geometric structure and self-organization of Sc patterns from this network perspective. Our network analysis shows that the Sc pattern is scale-invariant as a consequence of entropy maximization that is known as Lewis's Law (scaling parameter: 0.16) and is largely independent of the Sc regime (cloud-free vs. cloudy cell centers). Cells are, on average, hexagonal with a neighbor number variance of about 2, and larger cells tend to be surrounded by smaller cells, as described by an Aboav-Weaire parameter of 0.9. The network structure is neither completely random nor characteristic of natural convection. Instead, it emerges from Sc-specific versions of cell division and cell merging that are shaped by cell expansion. This is shown with a heuristic model of network dynamics that incorporates our physical understanding of cloud processes.
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Proceedings of the National Academy of Sciences of the United States of America, 114(40), 10578-10583.
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https://doi.org/10.1073/pnas.1706495114
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urn:sha256:3e493578bd2ab2b5ba84806671c1b797cd04bb40dfb25c050f6721b029e30781
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